text: from dffml import CSVSource, Features, Feature
  from dffml.noasync import train, accuracy, predict
  from dffml_model_daal4py.daal4pylr import DAAL4PyLRModel
  
  model = DAAL4PyLRModel(
      features=Features(Feature("f1", float, 1)),
      predict=Feature("ans", int, 1),
      directory="tempdir",
  )
  
  # Train the model
  train(model, "train.csv")
  
  # Assess accuracy (alternate way of specifying data source)
  print("Accuracy:", accuracy(model, CSVSource(filename="test.csv")))
  
  # Make prediction
  for i, features, prediction in predict(model, {"f1": 0.8, "ans": 0}):
      features["ans"] = prediction["ans"]["value"]
      print(features)
  